Earlier quoted context omitted.
I agree. Additionally, a company can own and update a business language of their own design at their own pace and need. Then they can use AI to translate from their controlled business language to the DSL needed (translation being an area it actually does well). In this way the LLM would only ever be going from General -> specific, which should keep it on the rails, and the business can keep its business logic stored…
> I agree. Additionally, a company can own and update a business language of their own design at their own pace and need. Yes, although I was more thinking of this being in most cases a SaaS offering because the implementation of the DSL needs solid non-LLM engineering. Larger companies will be able to afford an internal platform team, but most won't. > Now that said, there is still the actual engineering problem of…
I was thinking more about what I believe you describe as the "hard" engineers, and would say the power AI provides for mapping and translating will greatly benefit those teams as well with the right set-up. People are pushing for the "code for me" angle, but i think there will be a lot of opportunity to have LLMs take on a middle ground of syntax management while the engineers manage the system effects. for example, the engineer may be deciding whether to use a linked list or binary tree and the LLM is implementing it with the available code stack approved by the company.
A company that can successfully implement such an LLM opens up their talent pool from people who know their stack (or want to learn it) to people who know any stack